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Simulation and Prediction of Land Use/Cover Changes Based on CLUE-S and CA-Markov Models: A Case Study of a Typical Pastoral Area in Mongolia

Author

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  • Changqing Sun

    (Department of Geography, School of Arts and Sciences, National University of Mongolia, Ulaanbaatar 14200, Mongolia
    College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China)

  • Yulong Bao

    (College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China
    Inner Mongolia Key Laboratory of Remote Sensing & Geography Information System, Hohhot 010022, China)

  • Battsengel Vandansambuu

    (Department of Geography, School of Arts and Sciences, National University of Mongolia, Ulaanbaatar 14200, Mongolia)

  • Yuhai Bao

    (College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China
    Inner Mongolia Key Laboratory of Remote Sensing & Geography Information System, Hohhot 010022, China)

Abstract
Modeling and predicting land use/cover change (LUCC) and identifying its drivers have been a focus of research over the past few decades. In order to solve the problem of land resource degradation in typical pastoral areas, reveal the temporal and spatial evolution characteristics of LUCC, and the contradiction between man and land in sustainable development, we analyze the Gurvanbulag area of Bulgan province, Mongolia, where grassland degradation is relatively serious. The LUCC data in 2000, 2010 and 2019 were obtained through interpreting human-computer interaction. On this basis, the same binary logistic regression (BLR) results were input into the multi-criteria evaluation analytic hierarchy process (MCE_AHP) of CLUE-S and CA_Markov models. The Current Trends (CT) and Ecological Protection (EP) development scenarios were used to predict the temporal and spatial evolution characteristics of LUCC in 2030 and 2040. The results show: (1) both models can effectively simulate the LUCC in 2019, and the CLUE-S model was significantly better than the CA_Markov model. (2) From 2000 to 2019, the LUCC in this region was dominated by a decrease in water and the growth of grassland and other land, indicating that the region is at the risk of land resource degradation. (3) In a multi-scenario development study, by 2030 and 2040, both models predicted that the EP development scenario is more effective in protecting the local ecological environment and it is easier to achieve the sustainability of land resources, than the CT development scenario. Combined with local policy demands and the prediction results of restraining land resource degradation, CLUE-S was significantly higher than the CA_Markov model, indicating that in typical pastoral areas, the former is more in line with the need for sustainable development of the local ecological environment than the latter.

Suggested Citation

  • Changqing Sun & Yulong Bao & Battsengel Vandansambuu & Yuhai Bao, 2022. "Simulation and Prediction of Land Use/Cover Changes Based on CLUE-S and CA-Markov Models: A Case Study of a Typical Pastoral Area in Mongolia," Sustainability, MDPI, vol. 14(23), pages 1-21, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15707-:d:984440
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    References listed on IDEAS

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    1. Siqi Liu & Qing Yu & Chen Wei, 2019. "Spatial-Temporal Dynamic Analysis of Land Use and Landscape Pattern in Guangzhou, China: Exploring the Driving Forces from an Urban Sustainability Perspective," Sustainability, MDPI, vol. 11(23), pages 1-20, November.
    2. Peter Verburg & Bas Eickhout & Hans Meijl, 2008. "A multi-scale, multi-model approach for analyzing the future dynamics of European land use," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(1), pages 57-77, March.
    3. Mansour, Shawky & Al-Belushi, Mohammed & Al-Awadhi, Talal, 2020. "Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques," Land Use Policy, Elsevier, vol. 91(C).
    4. Rahel Hamad & Heiko Balzter & Kamal Kolo, 2018. "Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios," Sustainability, MDPI, vol. 10(10), pages 1-23, September.
    5. Wang, Quan & Wang, Haijun & Chang, Ruihan & Zeng, Haoran & Bai, Xuepiao, 2022. "Dynamic simulation patterns and spatiotemporal analysis of land-use/land-cover changes in the Wuhan metropolitan area, China," Ecological Modelling, Elsevier, vol. 464(C).
    6. Huang, Daquan & Huang, Jing & Liu, Tao, 2019. "Delimiting urban growth boundaries using the CLUE-S model with village administrative boundaries," Land Use Policy, Elsevier, vol. 82(C), pages 422-435.
    7. Ruci Wang & Ahmed Derdouri & Yuji Murayama, 2018. "Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area," Sustainability, MDPI, vol. 10(6), pages 1-18, June.
    8. Rui Zhou & Hao Zhang & Xin-Yue Ye & Xin-Jun Wang & Hai-Long Su, 2016. "The Delimitation of Urban Growth Boundaries Using the CLUE-S Land-Use Change Model: Study on Xinzhuang Town, Changshu City, China," Sustainability, MDPI, vol. 8(11), pages 1-16, November.
    9. David Sneath, 2003. "Land use, the environment and development in post-socialist Mongolia," Oxford Development Studies, Taylor & Francis Journals, vol. 31(4), pages 441-459.
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